Modelling and Removing the Gradient Artefact Using a Gradient Model Fit (GMF)

Glyn S. Spencer¹, Karen J. Mullinger¹, Andrew Peters¹, Richard Bowtell¹

The EEG gradient artefact (GA) is formed from a linear superposition of individual artefacts generated by the orthogonal gradients. Variations in position of the head and/or EEG leads scale the relative weighting of the artefact contribution from the different gradient channels. Here we verify this concept and use it to introduce a novel GA correction method, which is based on a gradient model fit (GMF). Our results show that GMF performs better than conventional GA correction methods at high frequency when subject movement occurs, potentially providing a more robust method for GA correction when investigating gamma (30-150Hz) frequency neuronal activity.